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Record W2319770611 · doi:10.13083/reveng.v21i2.347

DESEMPENHO AGRONÔMICO E ESTADO NUTRICIONAL DO CAPIM MOMBAÇA FERTIRRIGADO COM ÁGUAS RESIDUÁRIAS DE CURTUME

2013· article· pt· W2319770611 on OpenAlexaff
Pedro Rodrigues de Oliveira, Antônio Teixeira de Matos, Paola Alfonsa Vieira Lo Monaco

Bibliographic record

VenueRevista Engenharia na Agricultura - REVENG · 2013
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicGrowth and nutrition in plants
Canadian institutionsProbity Medical Research
Fundersnot available
KeywordsChemistryHorticultureAnimal scienceBiology

Abstract

fetched live from OpenAlex

Objetivou-se, com a realização deste trabalho, avaliar a produtividade e o estado nutricional do capim mombaça (Panicum Maximum cv. Mombaça) quando fertirrigado com a aplicação de diferentes doses de água residuária de curtume (ARC). Com base na composição química da água residuária foram estabelecidas as taxas de aplicação da ARC: T1: 0; T2: 1,5; T3: 3,0; T4: 5,0; T5: 10 e T6: 15 kg ha-1 de crômio. De acordo com os resultados obtidos, pôde-se concluir que a aplicação da ARC foi responsável pelo aumento no teor de proteína bruta do capim nos dois primeiros cortes e também na produtividade de matéria seca. Tanto a produtividade de matéria seca quanto a de proteína bruta foram maiores no corte 2, sendo estimados os maiores valores quando da aplicação das doses de 9,02 kg ha-1 de Cr (2.734 m3 ha-1 de ARC) e 10,08 kg ha-1 de Cr (3.055 m3 ha-1 de ARC), respectivamente. O aumento na dose de ARC proporcionou valores decrescentes na concentração potássio e crescentes na de sódio nas folhas do capim mombaça. Em relação ao comportamento do metal crômio, não foi observada influência dos tratamentos na sua concentração nas folhas. Em vista de se utilizar muito NaCl na salga das peles, o aumento na concentração de sódio nas plantas é aparentemente problema maior do que propriamente o proporcionado pelo crômio.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.224
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueRevista Engenharia na Agricultura - REVENGSame topicGrowth and nutrition in plantsFrench-language works237,207